The point of this post is to give you some guidance on what we’re looking for when we review the applications. I hope you find it helpful.
Back in November, I headed home from the office early and opened up 130 applications for the Data Study Group which coming up in December 2017.
Some of the applications were outstanding. We had students from mathematics, statistics, bioinformatics, computer science, engineering, political science, psychology and philosophy. There were data scientists working in startups and multinational corporations (and a few companies in between!) It was a joy to read how data science was being harnessed and advanced by so many interesting people.
But (there’s always a but) some of the applications were difficult to score.
I’ll summarise the questions you will be asked in the application form::
- What technical skills would you bring to your team?
- What collaborative skills would you bring to your team?
- What do you hope to personally achieve through your participation in the Data Study Group?
For the first two questions we also ask you to share with us some links that provide some evidence for your answers.
We ask about technical skills because we want to deliver the very best data science solutions to real world problems. There are lots of ways to evidence that you have technical skills, but a list of programming languages is not a great one. Think about how the challenge team would benefit from your expertise. What problems have you solved using these skills? Why might they be relevant for a fast-paced data study group week?
A great way to share evidence for your technical skills is to share links to GitHub repositories. We understand that not everyone is able to publicly share the code they’ve written, so a dropbox link, or a link to a google drive file, works very well. The best answers provide specific links to skills that were highlighted in the technical skills answer.
Another top tip from a busy person: check that the links work before you send them. Write up your application outside of the google form and send it to a friend. Make sure they can access all the files you want the reviewers to see.
Making sure all our DSG participants have fun and learn from each other is of equally high priority as our goal of delivering world class solutions.
I noticed when I read the December applications that most people answered a version of “What collaborative or interdisciplinary work have you done?” These answers missed a focus on how your team would benefit from having you there. Just because you have worked with others doesn’t mean you’re good at it. Show us how you will help complete a challenging project in one week.
Communication is key
Here’s my second top tip: clear communication is key. Your application itself is evidence of how well you can convey your expertise to an audience outside of your specialty. Can you bring out the best in others? Have you done this in the past? Can you be creative in how you evidence this understanding of your teammates’ motivations? (I think you can!) Do you have leadership or project management expertise? Make us excited to have you with us for the week!
Your answer to the question of what you want to get out of the Data Study Group contributes to your score in two distinct ways. The first is whether you understand what a data study group entails: are your expectations aligned with what can be achieved during the week? Have you accurately assessed how you can contribute and what you can learn?
We also want to test whether our Data Study Group is right for you. Are you looking to change the world when you graduate from your PhD? Do you want a taster of what industry collaboration would look like? Are the opportunities to work with real world data limited in your current position? Data Study Groups allow us to share the experience that we have very day at the Turing of working with great people from a huge range of backgrounds from around the world.
We look forward to hearing from you with your applications for our next Data Study Group.